scholarly journals On constraining the strength of the terrestrial CO<sub>2</sub> fertilization effect in an Earth system model

2016 ◽  
Author(s):  
V. K. Arora ◽  
J. F. Scinocca
Keyword(s):  
Carbon Cycle ◽  
Carbon Budget ◽  
Co2 Flux ◽  
Global Carbon Cycle ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Co2 Fertilization ◽  
Fertilization Effect ◽  
Global Carbon

Abstract. Earth system models (ESMs) explicitly simulate the interactions between the physical climate system components and biogeochemical cycles. Physical and biogeochemical aspects of ESMs are routinely compared against their observation-based counterparts to assess model performance and to evaluate how this performance is affected by ongoing model development. Here, we assess the performance of version 4.2 of the Canadian Earth system model against four, land carbon cycle focused, observation-based determinants of the global carbon cycle and the historical global carbon budget over the 1850–2005 period. Our objective is to constrain the strength of the terrestrial CO2 fertilization effect which is known to be the most uncertain of all carbon cycle feedbacks. The observation-based determinants include (1) globally-averaged atmospheric CO2 concentration, (2) cumulative atmosphere–land CO2 flux, (3) atmosphere–land CO2 flux for the decades of 1960s, 1970s, 1980s, 1990s and 2000s and (4) the amplitude of the globally-averaged annual CO2 cycle and its increase over the 1980 to 2005 period. The optimal simulation that satisfies constraints imposed by the first three determinants yields a net primary productivity (NPP) increase from ~ 58 Pg C yr−1 in 1850 to about ~ 74 Pg C yr−1 in 2005; an increase of ~ 27 % over the 1850–2005 period. The simulated loss in the global soil carbon amount due to anthropogenic land use change over the historical period is also broadly consistent with empirical estimates. Yet, it remains possible that these determinants of the global carbon cycle are insufficient to adequately constrain the historical carbon budget, and consequently the strength of terrestrial CO2 fertilization effect as it is represented in the model, given the large uncertainty associated with LUC emissions over the historical period.

scholarly journals Constraining the strength of the terrestrial CO<sub>2</sub> fertilization effect in the Canadian Earth system model version 4.2 (CanESM4.2)

2016 ◽  
Vol 9 (7) ◽  
pp. 2357-2376 ◽  
Author(s):  
Vivek K. Arora ◽  
John F. Scinocca
Keyword(s):  
Carbon Cycle ◽  
Carbon Budget ◽  
Co2 Flux ◽  
Global Carbon Cycle ◽  
System Model ◽  
Historical Period ◽  
Earth System ◽  
Co2 Fertilization ◽  
Fertilization Effect ◽  
Global Carbon

Abstract. Earth system models (ESMs) explicitly simulate the interactions between the physical climate system components and biogeochemical cycles. Physical and biogeochemical aspects of ESMs are routinely compared against their observation-based counterparts to assess model performance and to evaluate how this performance is affected by ongoing model development. Here, we assess the performance of version 4.2 of the Canadian Earth system model against four land carbon-cycle-focused, observation-based determinants of the global carbon cycle and the historical global carbon budget over the 1850–2005 period. Our objective is to constrain the strength of the terrestrial CO2 fertilization effect, which is known to be the most uncertain of all carbon-cycle feedbacks. The observation-based determinants include (1) globally averaged atmospheric CO2 concentration, (2) cumulative atmosphere–land CO2 flux, (3) atmosphere–land CO2 flux for the decades of 1960s, 1970s, 1980s, 1990s, and 2000s, and (4) the amplitude of the globally averaged annual CO2 cycle and its increase over the 1980 to 2005 period. The optimal simulation that satisfies constraints imposed by the first three determinants yields a net primary productivity (NPP) increase from  ∼  58 Pg C year−1 in 1850 to about  ∼  74 Pg C year−1 in 2005; an increase of  ∼  27 % over the 1850–2005 period. The simulated loss in the global soil carbon amount due to anthropogenic land use change (LUC) over the historical period is also broadly consistent with empirical estimates. Yet, it remains possible that these determinants of the global carbon cycle are insufficient to adequately constrain the historical carbon budget, and consequently the strength of terrestrial CO2 fertilization effect as it is represented in the model, given the large uncertainty associated with LUC emissions over the historical period.

Reconstructions and predictions of the global carbon cycle with an emission-driven Earth System Model

2021 ◽  
Author(s):  
Hongmei Li ◽  
Tatiana Ilyina ◽  
Tammas Loughran ◽  
Julia Pongratz
Keyword(s):  
Growth Rate ◽  
Carbon Cycle ◽  
Carbon Budget ◽  
Global Carbon Cycle ◽  
System Model ◽  
Earth System ◽  
Global Carbon Budget ◽  
Predictive Skill ◽  
Atmospheric Carbon ◽  
Global Carbon

&lt;p&gt;The global carbon budget including CO&lt;sub&gt;2&lt;/sub&gt; fluxes among different reservoirs and atmospheric carbon growth rate vary substantially in interannual to decadal time-scales. Reconstructing and predicting the variable global carbon cycle is of essential value of tracing the fate of carbon and the corresponding climate and ecosystem changes. For the first time, we extend our prediction system based on the Max Planck Institute Earth system model (MPI-ESM) from concentration-driven to emission-driven taking into account the interactive carbon cycle and hence enabling prognostic atmospheric carbon increment.&amp;#160;&lt;/p&gt;&lt;p&gt;By assimilating atmospheric and oceanic observational data products into MPI-ESM decadal prediction system, we can reproduce the observed variations of the historical global carbon cycle globally. The reconstruction from the fully coupled model enables quantification of global carbon budget within a close Earth system and therefore avoids the budget imbalance term of budgeting the carbon with standalone models. Our reconstructions of carbon budget provide a novel approach for supporting global carbon budget and understanding the dominating processes. Retrospective predictions based on the &amp;#160;emission-driven hindcasts, which are initiated from the reconstructions, show predictive skill in the atmospheric carbon growth rate, air-sea CO&lt;sub&gt;2&lt;/sub&gt; fluxes, and air-land CO&lt;sub&gt;2&lt;/sub&gt; fluxes. The air-sea CO&lt;sub&gt;2&lt;/sub&gt; fluxes have higher predictive skill up to 5 years, and the air-land CO&lt;sub&gt;2&lt;/sub&gt; fluxes and atmospheric carbon growth rate show predictive skill of 2 years. Our results also suggest predictions based on Earth system models enable reproducing and further predicting the evolution of atmospheric CO&lt;sub&gt;2&lt;/sub&gt; concentration changes. The earth system predictions will provide valuable inputs for understanding the global carbon cycle and supporting climate relevant policy development.&amp;#160;&lt;/p&gt;

Representing Arctic coastal erosion in the Max Planck Institute Earth System Model (MPI-ESM)

2020 ◽  
Author(s):  
David Marcolino Nielsen ◽  
Johanna Baehr ◽  
Victor Brovkin ◽  
Mikhail Dobrynin
Keyword(s):  
Carbon Cycle ◽  
Sea Ice ◽  
Coastal Erosion ◽  
Global Carbon Cycle ◽  
System Model ◽  
The Arctic ◽  
Earth System ◽  
Max Planck ◽  
Erosion Rates ◽  
Global Carbon

&lt;p&gt;The Arctic has warmed twice as fast as the globe and sea-ice extent has decreased, causing permafrost to thaw and the duration of the open-water period to extend. This combined effect increases the vulnerability of the Arctic coast to erosion, which in turn releases substantial amounts of carbon to both the ocean and the atmosphere, potentially contributing to further warming due to a positive climate-carbon cycle feedback. Therefore, Arctic coastal erosion is an important process of the global carbon cycle.&lt;/p&gt;&lt;p&gt;Comprehensive modelling studies exploring Arctic coastal erosion within the Earth system are still in their infancy. Here, we describe the development of a semi-empirical Arctic coastal erosion model and its coupling with the Max Planck Institute Earth System Model (MPI-ESM). We also present preliminary results for historical and future climate projections of coastal erosion rates in the Arctic. The coupling consists on the exchange of a combination of driving forcings from the atmosphere and the ocean, such as surface air temperature, winds and sea-ice concentration, which result in annual coastal erosion rates. In a further setp, organic matter from the eroded permafrost is provided to the ocean biogeochemistry model and, consequently, to the global carbon cycle including atmospheric CO&lt;sub&gt;2&lt;/sub&gt;.&lt;/p&gt;

scholarly journals The global carbon cycle in the Canadian Earth system model (CanESM1): Preindustrial control simulation

2010 ◽  
Vol 115 (G3) ◽  
Author(s):  
J. R. Christian ◽  
V. K. Arora ◽  
G. J. Boer ◽  
C. L. Curry ◽  
K. Zahariev ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Global Carbon Cycle ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Control Simulation ◽  
Global Carbon

scholarly journals A global CO<sub>2</sub> flux dataset (2015–2019) inferred from OCO-2 retrievals using the Tan-Tracker inversion system

2021 ◽  
Author(s):  
Zhe Jin ◽  
Xiangjun Tian ◽  
Rui Han ◽  
Yu Fu ◽  
Xin Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Carbon Cycle ◽  
Carbon Flux ◽  
Carbon Budget ◽  
Terrestrial Ecosystem ◽  
Carbon Fluxes ◽  
Global Carbon Cycle ◽  
Ocean Carbon ◽  
Global Carbon ◽  
Regional Fluxes

Abstract. Accurate assessment of the various sources and sinks of carbon dioxide (CO2), especially terrestrial ecosystem and ocean fluxes with high uncertainties, is important for understanding of the global carbon cycle, supporting the formulation of climate policies, and projecting future climate change. Satellite retrievals of the column-averaged dry air mole fractions of CO2 (XCO2) are being widely used to improve carbon flux estimation due to their broad spatial coverage. However, there is no consensus on the robust estimates of regional fluxes. In this study, we present a global and regional resolved terrestrial ecosystem carbon flux (NEE) and ocean carbon flux dataset for 2015–2019. The dataset was generated using the Tan-Tracker inversion system by assimilating Observing Carbon Observatory 2 (OCO-2) column CO2 retrievals. The posterior NEE and ocean carbon fluxes were comprehensively validated by comparing posterior simulated CO2 concentrations with OCO-2 independent retrievals and Total Carbon Column Observing Network (TCCON) measurements. The validation showed that posterior carbon fluxes significantly improved the modelling of atmospheric CO2 concentrations, with global mean biases of 0.33 ppm against OCO-2 retrievals and 0.12 ppm against TCCON measurements. We described the characteristics of the dataset at global, regional, and Tibetan Plateau scales in terms of the carbon budget, annual and seasonal variations, and spatial distribution. The posterior 5-year annual mean global atmospheric CO2 growth rate was 5.35 PgC yr−1, which was within the uncertainty of the Global Carbon Budget 2020 estimate (5.49 PgC yr−1). The posterior annual mean NEE and ocean carbon fluxes were −4.07 and −3.33 PgC yr−1, respectively. Regional fluxes were analysed based on TransCom partitioning. All 11 land regions acted as carbon sinks, except for Tropical South America, which was almost neutral. The strongest carbon sinks were located in Boreal Asia, followed by Temperate Asia and North Africa. The entire Tibetan Plateau ecosystem was estimated as a carbon sink, taking up −49.52 TgC yr−1 on average, with the strongest sink occurring in eastern alpine meadows. These results indicate that our dataset captures surface carbon fluxes well and provides insight into the global carbon cycle. The dataset can be accessed at https://doi.org/10.11888/Meteoro.tpdc.271317 (Jin et al., 2021).

scholarly journals Trivial improvements of predictive skill due to direct reconstruction of global carbon cycle

2021 ◽  
Author(s):  
Aaron Spring ◽  
István Dunkl ◽  
Hongmei Li ◽  
Victor Brovkin ◽  
Tatiana Ilyina
Keyword(s):  
Carbon Cycle ◽  
Initial Conditions ◽  
Co2 Flux ◽  
Global Carbon Cycle ◽  
Atmospheric Co2 ◽  
State Variables ◽  
Predictive Skill ◽  
Perfect Model ◽  
Prediction Systems ◽  
Global Carbon

Abstract. State-of-the-art carbon cycle prediction systems are initialized from reconstruction simulations in which state variables of the climate system are assimilated. While currently only the physical state variables are assimilated, biogeochemical state variables adjust to the state acquired through this assimilation indirectly instead of being assimilated themselves. In the absence of comprehensive biogeochemical reanalysis products, such approach is pragmatic. Here we evaluate a potential advantage of having perfect carbon cycle observational products to be used for direct carbon cycle reconstruction. Within an idealized perfect-model framework, we define 50 years of a control simulation under pre-industrial CO2 levels as our target representing observations. We nudge variables from this target onto arbitrary initial conditions 150 years later mimicking an assimilation simulation generating initial conditions for hindcast experiments of prediction systems. We investigate the tracking performance, i.e. bias, correlation and root-mean-square-error between the reconstruction and the target, when nudging an increasing set of atmospheric, oceanic and terrestrial variables with a focus on the global carbon cycle explaining variations in atmospheric CO2. We compare indirect versus direct carbon cycle reconstruction against a resampled threshold representing internal variability. Afterwards, we use these reconstructions to initialize ensembles to assess how well the target can be predicted after reconstruction. Interested in the ability to reconstruct global atmospheric CO2, we focus on the global carbon cycle reconstruction and predictive skill. We find that indirect carbon cycle reconstruction through physical fields reproduces the target variations on a global and regional scale much better than the resampled threshold. While reproducing the large scale variations, nudging introduces systematic regional biases in the physical state variables, on which biogeochemical cycles react very sensitively. Global annual surface oceanic pCO2 initial conditions are indirectly reconstructed with an anomaly correlation coefficient (ACC) of 0.8 and debiased root mean square error (RMSE) of 0.3 ppm. Direct reconstruction slightly improves initial conditions in ACC by +0.1 and debiased RMSE by −0.1 ppm. Indirect reconstruction of global terrestrial carbon cycle initial conditions for vegetation carbon pools track the target by ACC of 0.5 and debiased RMSE of 0.5 PgC. Direct reconstruction brings negligible improvements for air-land CO2 flux. Global atmospheric CO2 is indirectly tracked by ACC of 0.8 and debiased RMSE of 0.4 ppm. Direct reconstruction of the marine and terrestrial carbon cycles improves ACC by 0.1 and debiased RMSE by −0.1 ppm. We find improvements in global carbon cycle predictive skill from direct reconstruction compared to indirect reconstruction. After correcting for mean bias, indirect and direct reconstruction both predict the target similarly well and only moderately worse than perfect initialization after the first lead year. Our perfect-model study shows that indirect carbon cycle reconstruction yields satisfying initial conditions for global CO2 flux and atmospheric CO2. Direct carbon cycle reconstruction adds little improvements in the global carbon cycle, because imperfect reconstruction of the physical climate state impedes better biogeochemical reconstruction. These minor improvements in initial conditions yield little improvement in initialized perfect-model predictive skill. We label these minor improvements due to direct carbon cycle reconstruction trivial, as mean bias reduction yields similar improvements. As reconstruction biases in real-world prediction systems are even stronger, our results add confidence to the current practice of indirect reconstruction in carbon cycle prediction systems.

scholarly journals The validity of floating chambers in quantifying CO2 flux from headwater streams

2020 ◽  
Author(s):  
M. J. Rawitch ◽  
G. L. Macpherson ◽  
A. E. Brookfield
Keyword(s):  
Carbon Cycle ◽  
Headwater Streams ◽  
Co2 Flux ◽  
Field Measurements ◽  
Global Carbon Cycle ◽  
Low Velocity ◽  
Flume Experiments ◽  
Moderate Range ◽  
Co2 Degassing ◽  
Global Carbon

Abstract The amount of CO2 exiting headwater streams through degassing plays an important role in the global carbon cycle, yet quantification of CO2 degassing remains challenging because of the morphology of headwater streams and because of uncertainty about whether floating or suspended chambers provide valid measurements in moving water. We show that experiments using large and small floating chambers in flowing water over a moderate range of water velocities (0.13–0.23 m s−1) in a laboratory flume resulted in similar k600s to published field measurements with similar water velocities. We confirmed the flume experiments with paired stirred-still beaker experiments, where resulting k600s fell within the extrapolated trend of the flume experiments. We propose that the floating chambers can provide good estimates of CO2 degassing, particularly in shallow, low-velocity, morphologically complex headwater streams, permitting quantification of this important contributor to the global carbon cycle.

scholarly journals The global carbon budget 1959–2011

2013 ◽  
Vol 5 (1) ◽  
pp. 165-185 ◽  
Author(s):  
C. Le Quéré ◽  
R. J. Andres ◽  
T. Boden ◽  
T. Conway ◽  
R. A. Houghton ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Carbon Cycle ◽  
Co2 Emissions ◽  
Carbon Budget ◽  
Co2 Concentration ◽  
Global Carbon Cycle ◽  
Atmospheric Co2 ◽  
Global Carbon Budget ◽  
Atmospheric Co2 Concentration ◽  
Global Carbon

Abstract. Accurate assessments of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. Finally, the global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms. For the last decade available (2002–2011), EFF was 8.3 &amp;pm; 0.4 PgC yr−1, ELUC 1.0 &amp;pm; 0.5 PgC yr−1, GATM 4.3 &amp;pm; 0.1 PgC yr−1, SOCEAN 2.5 &amp;pm; 0.5 PgC yr−1, and SLAND 2.6 &amp;pm; 0.8 PgC yr−1. For year 2011 alone, EFF was 9.5 &amp;pm; 0.5 PgC yr−1, 3.0 percent above 2010, reflecting a continued trend in these emissions; ELUC was 0.9 &amp;pm; 0.5 PgC yr−1, approximately constant throughout the decade; GATM was 3.6 &amp;pm; 0.2 PgC yr−1, SOCEAN was 2.7 &amp;pm; 0.5 PgC yr−1, and SLAND was 4.1 &amp;pm; 0.9 PgC yr−1. GATM was low in 2011 compared to the 2002–2011 average because of a high uptake by the land probably in response to natural climate variability associated to La Niña conditions in the Pacific Ocean. The global atmospheric CO2 concentration reached 391.31 &amp;pm; 0.13 ppm at the end of year 2011. We estimate that EFF will have increased by 2.6% (1.9–3.5%) in 2012 based on projections of gross world product and recent changes in the carbon intensity of the economy. All uncertainties are reported as &amp;pm;1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_V2013). Global carbon budget 2013

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